Review of Prognostic Expression Markers for Clear Cell Renal Cell Carcinoma

Zebularine showed anti-tumor efficacy in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) has the highest morbidity among renal cell carcinoma (RCC) subtypes. While existing clinical pharmacological intervention strategies have achieved certain efficacy, challenges including inevitable drug resistance and intricate immune heterogeneity of ccRCC continue to hinder their biomedical application. Therefore, developing novel immunotherapeutic agents and identifying patients who can gain the greatest benefits from these therapies are urgent issues.

Methods

To address these challenges, mRNA expression profile and clinical data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These data were integrated and randomly allocated into training and test sets. Immune-related differentially expressed genes (IRDEGs) were used to construct an immune-related gene prognostic index (IRGPI). Both prognostic performance metrics and immune phenotyping were employed to evaluate the effectiveness of the model. Furthermore, model IRDEGs (mIRDEGs) in two risk subgroups were leveraged to select potential therapeutic compounds. Afterwards, network pharmacology and molecular docking techniques were used to elucidate the anti-cancer mechanisms of Zebularine (Zeb). Finally, the anti-cancer efficacy of Zeb was validated through in vivo and in vitro experiments.

Results

Our constructed IRGPI exhibited superior prognostic performance. The drug screening revealed Zeb potentially targets the PI3K-Akt signaling pathway to exert its anti-cancer effects. Subsequent experimental validation corroborated these theoretical findings.

Conclusion

This study presents a prognostic model to evaluate immune cell infiltration and predict the prognosis of ccRCC patients. The identified small molecule compound provides a novel therapeutic avenue for treating ccRCC patients.

French AFU Cancer Committee Guidelines - Update 2024-2026: Management of kidney cancer

OBJECTIVE

To update the French recommendations for the management of kidney cancer.

METHODS

A systematic review of the literature was conducted for the period from 2014 to 2024. The most relevant articles concerning the diagnosis, classification, surgical treatment, medical treatment, and follow-up of kidney cancer were selected and incorporated into the recommendations. The recommendations have been updated specifying the level of evidence (strong or weak).

RESULTS

Kidney cancer following prolonged occupational exposure to trichloroethylene should be considered an occupational disease. The reference examination for the diagnosis and staging of kidney cancer is the contrast-enhanced thoraco-abdominal CT scan. PET scans are not indicated in the staging of kidney cancer. Percutaneous biopsy is recommended in situations where its results will influence therapeutic decisions. It should be used to reduce the number of surgeries for benign tumors, particularly avoiding unnecessary radical nephrectomies. Kidney tumors should be classified according to the pTNM 2017 classification, the WHO 2022 classification, and the ISUP nucleolar grade. Metastatic kidney cancers should be classified according to IMDC criteria. Surveillance of tumors smaller than 2cm should be prioritized and can be offered regardless of patient age. Robot-assisted laparoscopic partial nephrectomy is the reference surgical treatment for T1 tumors. Ablative therapies and surveillance are options for elderly patients with comorbidities for tumors larger than 2cm. Stereotactic radiotherapy is an option to discuss for treating localized kidney tumors in patients not eligible for other treatments. Radical nephrectomy is the first-line treatment for locally advanced localized cancers. Pembrolizumab is recommended for patients at high risk of recurrence after surgery for localized kidney cancer. In metastatic patients, cytoreductive nephrectomy can be immediate in cases of good prognosis, delayed in cases of intermediate or poor prognosis for patients stabilized by medical treatment, or as "consolidation" in patients with complete or major partial response at metastatic sites after systemic treatment. Surgical or local treatment of metastases can be proposed for single lesions or oligometastases. Recommended first-line drugs for metastatic clear cell renal carcinoma are combinations of axitinib/pembrolizumab, nivolumab/ipilimumab, nivolumab/cabozantinib, and lenvatinib/pembrolizumab. Patients with non-clear cell metastatic kidney cancer should be presented to the CARARE Network and prioritized for inclusion in clinical trials.

CONCLUSION

These updated recommendations are a reference that will enable French and French-speaking practitioners to optimize their management of kidney cancer.

Prognostic factors and prognostic model of non-metastatic clear cell renal cell carcinoma

INTRODUCTION

Although there are some established prognostic evaluation models for clear cell renal cell carcinoma (ccRCC), more robust postoperative prognostic evaluation model is urgently needed. Our study intends to explore new clinical and pathological prognostic factors related to non-metastatic ccRCC, which help to establish a better prognostic risk evaluation model in non-metastatic ccRCC.

PATIENTS AND METHODS

A retrospective cohort study was conducted in non-metastatic ccRCC patients spanning from 2010 to 2018. Clinical and pathological factors of these patients were collected. Cox regression analysis was employed to assess the relationship between these factors and disease-free survival (DFS), and a nomogram risk prediction model was also constructed.

RESULTS

A total of 1467 patients were ultimately included, comprising 994 men (67.8%), with 800 patients aged between 40 and 60 years old (54.5%), and 80 patients (5.5%) experiencing relapse or metastasis of ccRCC within three years after operation. The follow-up duration ranged from 39 to 146 months. Univariate and multivariate Cox regression analysis identified five independent prognostic factors of DFS (P < 0.05) including sex, tumor maximum diameter, T stage, lactate dehydrogenase (LDH), and basophils. Leveraging these five factors, we established a prognostic evaluation model demonstrating good predictive efficacy.

CONCLUSION

Male, tumor maximum diameter, T stage, LDH, and basophils serve as prognostic indicators for DFS in patients with non-metastatic ccRCC. Patients with high scores based on our model exhibit an elevated likelihood of recurrence or metastasis, thereby potentially selecting postoperative patients with high risk for adjuvant therapy.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Diagnostic, predictive and prognostic molecular biomarkers in clear cell renal cell carcinoma: A retrospective study

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of kidney cancer. Many patients are diagnosed at advanced stages, making early detection crucial. Unfortunately, there are currently no noninvasive tests for ccRCC, emphasizing the need for new biomarkers. Additionally, ccRCC often develops resistance to treatments like radiotherapy and chemotherapy. Identifying biomarkers that predict treatment outcomes is vital for personalized care. The integration of artificial intelligence (AI), multi-omics analysis, and computational biology holds promise in bolstering detection precision and resilience, opening avenues for future investigations. The amalgamation of radiogenomics and biomaterial-basedimmunomodulation signifies a revolutionary breakthrough in diagnostic medicine. This review summarizes existing literature and highlights emerging biomarkers that enhance diagnostic, predictive, and prognostic capabilities for ccRCC, setting the stage for future clinical research.

The single-cell evolution trajectory presented different hypoxia heterogeneity to reveal the carcinogenesis of genes in clear cell renal cell carcinoma: Based on multiple omics and real experimental verification

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is the most prevalent and aggressive subtype of renal cell carcinoma, originating from renal tubular epithelial cells in the kidney. Hypoxia proves to be a feature commonly observed in solid tumors, leading to increased resistance to treatment and tumor progression.

METHODS

scRNA-seq data were procured from GSE159115 data set. We utilized UMAP and NMF algorithm for clustering and dimensionality reduction. The FindAllMarkers function was used to compare various groups and identify potential hypoxia marker genes. A series of in vitro experiments, including CFA, flow cytometry targeting cell cycle, CCK-8, and EDU, was applied to investigate how ANGPTL4 regulated the ccRCC progression. Two cell lines of ccRCC cells, 786-O and Caki, were used for si-ANGPTL4 transfection.

RESULTS

We annotated a total of a total of 6 cell clusters, namely ccRCC malignant cells, T cells, endothelial cells, myeloid cells, smooth muscle cells, and B cells. We observed higher levels of hypoxia-score in the ccRCC malignant cells, while lowest hypoxia-score in T and B cells. We detected multiple hypoxia-related subclusters of TME cells in ccRCC, among which S100A4 CD8+ T cells and nonhypoxia CD8+ T cells were found with a marked elevation of T cell inhibitory gene score. We identified that ANGPTL4+ endothelial cells might function as an integrative role in tumor angiogenesis. Multiple TME subclusters showed high potency in stratification of the prognosis of ccRCC patients. Moreover, by a series of in vitro experiment, we found ANGPTL4 regulated the ccRCC cell proliferation, probably through ERK/P38 pathway.

CONCLUSION

We discerned multiple hypoxia-related subclusters of TME cells in ccRCC, which displayed distinct functional features and great potency in predicting prognosis of ccRCC patients. We identified the role of ANGPTL4 in regulating ccRCC proliferation via ERK/p38 pathway.

Identification of potential biomarkers for progression and prognosis of renal clear cell carcinoma by comprehensive bioinformatics analysis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cell carcinoma (RCC), and effective biomarkers will improve diagnosis and treatment.

OBJECTIVE

This study investigated NPEPL1 expression in ccRCC through public databases and clinical samples and assessed its correlation with clinicopathological features and patient prognosis.

METHOD

Data from The Cancer Genome Atlas and clinical specimens were gathered, NPEPL1 expression levels were analyzed; a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of NPEPL1; and clinicopathological data was used to study the correlations between expression and clinical parameters. NPEPL1's prognostic value was appraised using a Kaplan-Meier (K-M) survival curve, Cox regression analysis, and a nomogram model; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differently expressed genes between tissues with high and low NPEPL1 expression were used to estimate the underlying mechanisms involved.

RESULTS

NPEPL1 was significantly higher-expressed in ccRCC tissue. ROC analysis showed that NPEPL1 had noteworthy diagnostic efficacy. NPEPL1 expression was closely related to clinicopathological parameters, such as T and M stage. K-M analysis showed that overall survival was significantly shortened with high NPEPL1 expression. Cox regression analysis showed that NPEPL1 expression was an independent risk factor predicting overall survival. The nomogram showed a significantly high clinical value in predicting the 1-, 3-, and 5-year survival probabilities in ccRCC. GO and KEGG enrichment analysis suggested that NPEPL1 may promote the occurrence and development of ccRCC via the Ras signaling and other pathways.

CONCLUSION

NPEPL1 expression in ccRCC was higher than that in normal kidney tissues and was significantly associated with advanced clinical stage and poor prognosis. Therefore, NPEPL1 is a promising prognostic biomarker.

Assessment of Ki-67 proliferation index in prognosis prediction in patients with nonmetastatic clear cell renal cell carcinoma and tumor thrombus

PURPOSE

To determine the optimal cut-off value of Ki-67 for predicting the survival of patients with clear cell renal cell carcinoma (ccRCC) and tumor thrombus and to explore the correlation between Ki-67 expression and pathological features.

PATIENTS AND METHODS

We retrospectively analyzed Ki-67 immunohistochemical staining of ccRCC and tumor thrombus resected from February 2006 to February 2022. The survival rate was evaluated using the Kaplan-Meier method. The optimal cut-off value of the Ki-67 expression for predicting survival was determined by the minimum P-value method. Clinicopathological data were compared based on Ki-67 status (low versus high expression). Univariate and multivariate Cox regression analysis was used to explore independent predictors.

RESULTS

A total of 202 patients (median age, 58 years [IQR, 52-65 years], 147 men) with ccRCC and tumor thrombus were included in the study. The optimal cut-off value of Ki-67 for predicting survival was 30%. 159 (78.7%) and 43 (21.3%) patients were included in the low-expression and high-expression groups. Patients with Ki-67 high expression had significantly worse recurrence-free survival (P < 0.001) and cancer-specific survival (P < 0.001). Ki-67 high expression was associated with adverse pathological features, including tumor necrosis, ISUP nuclear grade, sarcomatoid differentiation, perirenal fat invasion, renal pelvis invasion, and inferior vena cava wall invasion (all P < 0.050). Ki-67 expression ≥ 30% (P = 0.016), tumor side (P = 0.003), diabetes (P = 0.040), blood loss (P = 0.016), inferior vena cava wall invasion (P = 0.016), and sarcomatoid differentiation (P = 0.014) were independent predictors of cancer-specific survival.

CONCLUSION

The optimal cut-off level of Ki-67 in predicting the prognosis of ccRCC and tumor thrombus was 30%. The high expression of Ki-67 was associated with the aggressive pathological phenotype and poor prognosis.

Therapeutic Efficacy of YM155 to Regulate an Epigenetic Enzyme in Major Subtypes of RCC

Renal cell carcinoma (RCC) is the most common type of kidney cancer and includes more than 10 subtypes. Compared to the intensively investigated clear cell RCC (ccRCC), the underlying mechanisms and treatment options of other subtypes, including papillary RCC (pRCC) and chromogenic RCC (chRCC), are limited. In this study, we analyzed the public databases for ccRCC, pRCC, and chRCC and found that BIRC5 was commonly overexpressed in a large cohort of pRCC and chRCC patients as well as ccRCC and was closely related to the progression of RCCs. We investigated the potential of BIRC5 as a therapeutic target for these three types of RCCs. Loss and gain of function studies showed the critical role of BIRC5 in cancer growth. YM155, a BIRC5 inhibitor, induced a potent tumor-suppressive effect in the three types of RCC cells and xenograft models. To determine the mechanism underlying the anti-tumor effects of YM155, we examined epigenetic modifications in the BIRC5 promoter and found that histone H3 lysine 27 acetylation (H3K27Ac) was highly enriched on the promoter region of BIRC5. Chromatin-immunoprecipitation analysis revealed that H3K27Ac enrichment was significantly decreased by YM155. Immunohistochemistry of xenografted tissue showed that overexpression of BIRC5 plays an important role in malignancy in RCC. Furthermore, high expression of P300 was significantly associated with the progression of RCC. Our findings demonstrate the P300-H3K27Ac-BIRC5 cascade in three types of RCC and provide a therapeutic path for future research on RCC.

Lipid metabolism-related gene expression in the immune microenvironment predicts prognostic outcomes in renal cell carcinoma

Background

Rates of renal cell carcinoma (RCC) occurrence and mortality are steadily rising. In an effort to address this issue, the present bioinformatics study was developed with the goal of identifying major lipid metabolism biomarkers and immune infiltration characteristics associated with RCC cases.

Methods

The Cancer Genome Atlas (TCGA) and E-MTAB-1980 were used to obtain matched clinical and RNA expression data from patients diagnosed with RCC. A LASSO algorithm and multivariate Cox regression analyses were employed to design a prognostic risk model for these patients. The tumor immune microenvironment (TIME) in RCC patients was further interrogated through ESTIMATE, TIMER, and single-cell gene set enrichment analysis (ssGSEA) analyses. Gene Ontology (GO), KEGG, and GSEA enrichment approaches were further employed to gauge the mechanistic basis for the observed results. Differences in gene expression and associated functional changes were then validated through appropriate molecular biology assays.

Results

Through the approach detailed above, a risk model based on 8 genes associated with RCC patient overall survival and lipid metabolism was ultimately identified that was capable of aiding in the diagnosis of this cancer type. Poorer prognostic outcomes in the analyzed RCC patients were associated with higher immune scores, lower levels of tumor purity, greater immune cell infiltration, and higher relative immune status. In GO and KEGG enrichment analyses, genes that were differentially expressed between risk groups were primarily related to the immune response and substance metabolism. GSEA analyses additionally revealed that the most enriched factors in the high-risk group included the stable internal environment, peroxisomes, and fatty acid metabolism. Subsequent experimental validation in vitro and in vivo revealed that the most significantly differentially expressed gene identified herein, ALOX5, was capable of suppressing RCC tumor cell proliferation, invasivity, and migration.

Conclusion

In summary, a risk model was successfully established that was significantly related to RCC patient prognosis and TIME composition, offering a robust foundation for the development of novel targeted therapeutic agents and individualized treatment regimens. In both immunoassays and functional analyses, dysregulated lipid metabolism was associated with aberrant immunological activity and the reprogramming of fatty acid metabolic activity, contributing to poorer outcomes.

Supervised Learning and Multi-Omics Integration Reveals Clinical Significance of Inner Membrane Mitochondrial Protein (IMMT) in Prognostic Prediction, Tumor Immune Microenvironment and Precision Medicine for Kidney Renal Clear Cell Carcinoma

Kidney renal clear cell carcinoma (KIRC) accounts for approximately 75% of all renal cancers. The prognosis for patients with metastatic KIRC is poor, with less than 10% surviving five years after diagnosis. Inner membrane mitochondrial protein (IMMT) plays a crucial role in shaping the inner mitochondrial membrane (IMM), regulation of metabolism and innate immunity. However, the clinical relevance of IMMT in KIRC is not yet fully understood, and its role in shaping the tumor immune microenvironment (TIME) remains unclear. This study aimed to investigate the clinical significance of IMMT in KIRC using a combination of supervised learning and multi-omics integration. The supervised learning principle was applied to analyze a TCGA dataset, which was downloaded and split into training and test datasets. The training dataset was used to train the prediction model, while the test and the entire TCGA dataset were used to evaluate its performance. Based on the risk score, the cutoff between the low and high IMMT group was set at median value. A Kaplan-Meier curve, receiver operating characteristic (ROC) curve, principal component analysis (PCA) and Spearman's correlation were conducted to evaluate the prediction ability of the model. Gene Set Enrichment Analysis (GSEA) was used to investigate the critical biological pathways. Immunogenicity, immunological landscape and single-cell analysis were performed to examine the TIME. Databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were employed for inter-database verification. Pharmacogenetic prediction was analyzed via single-guide RNA (sgRNA)-based drug sensitivity screening using Q-omics v.1.30. Low expressions of IMMT in tumor predicted dismal prognosis in KIRC patients and correlated with KIRC progression. GSEA revealed that low expressions of IMMT were implicated in mitochondrial inhibition and angiogenetic activation. In addition, low IMMT expressions had associations with reduced immunogenicity and an immunosuppressive TIME. Inter-database verification corroborated the correlation between low IMMT expressions, KIRC tumors and the immunosuppressive TIME. Pharmacogenetic prediction identified lestaurtinib as a potent drug for KIRC in the context of low IMMT expressions. This study highlights the potential of IMMT as a novel biomarker, prognostic predictor and pharmacogenetic predictor to inform the development of more personalized and effective cancer treatments. Additionally, it provides important insights into the role of IMMT in the mechanism underlying mitochondrial activity and angiogenesis development in KIRC, which suggests IMMT as a promising target for the development of new therapies.

Characterization of Tumor and Immune Tumor Microenvironment of Primary Tumors and Metastatic Sites in Advanced Renal Cell Carcinoma Patients Based on Response to Nivolumab Immunotherapy: Preliminary Results from the Meet-URO 18 Study

BACKGROUND

Prognostic and predictive factors for patients with metastatic renal cell carcinoma (mRCC) treated with immunotherapy are highly warranted, and the immune tumor microenvironment (I-TME) is under investigation.

METHODS

The Meet-URO 18 was a multicentric retrospective study assessing the I-TME in mRCC patients treated with ≥2nd-line nivolumab, dichotomized into responders and non-responders according to progression-free survival (≥12 months and ≤3 months, respectively). The primary objective was to identify differential immunohistochemical (IHC) patterns between the two groups. Lymphocyte infiltration and the expressions of different proteins on tumor cells (CD56, CD15, CD68, and ph-mTOR) were analyzed. The expression of PD-L1 was also assessed.

RESULTS

A total of 116 tumor tissue samples from 84 patients (59% were primary tumors and 41% were metastases) were evaluated. Samples from responders (N = 55) were significantly associated with lower expression of CD4+ T lymphocytes and higher levels of ph-mTOR and CD56+ compared with samples from non-responders (N = 61). Responders also showed a higher CD3+ expression (p = 0.059) and CD8+/CD4+ ratio (p = 0.084). Non-responders were significantly associated with a higher percentage of clear cell histology and grading.

CONCLUSIONS

Differential IHC patterns between the tumors in patients who were responders and non-responders to nivolumab were identified. Further investigation with genomic analyses is planned.

NEK2 is associated with poor prognosis of clear cell renal cell carcinoma and promotes tumor cell growth and metastasis

BACKGROUND

Never in Mitosis gene-A(NIMA)-related Kinase 2 (NEK2) is a critical player in themitotic processes. NEK2 is highly expressed in many kindsof human cancers and has been shown toparticipatein drug resistance, tumorigenesis, and tumor progression. However, the expression or function of NEK2 in clear cell renal cell carcinoma (ccRCC)hasnot yet been investigated.

METHODS

Weused TCGA databaseto study the NEK2 expression in ccRCC. The expression of NEK2 in tumor tissuesand adjacent tissueswas examined by immunohistochemistry. We also analysed the correlation between NEK2 expression and clinical parametersofccRCC. The mRNA and protein level of NEK2 expression were semi-quantifiedby qRT-PCR and western blotting analysis. Following NEK2 knockdown by RNA interference in Caki-1cells, whileNEK2 overexpression in A489 cells, CCK8and transwell assay was used to confirmtheproliferation, migration and invasion, respectively.Finally, our in vivo study were carried out using nudemice to establish mouse model for kidney cancer.

RESULTS

We observed elevated expression of NEK2 both in ccRCCtumor tissues and cell lines. Together with clinical and pathological features, our analysis indicated a clear association of clinical outcomes between ccRCC patients with high and lowNEK2expression. Our in vitro studies demonstratedthat NEK2 knockdowninhibits the proliferation,migrationand invasion of Caki-1cells, oppositely, overexpressionof NEK2 promotes the proliferation, migrationand invasion of A489cells.In the end, our animal study demonstrated that deletion of NEK2 expression could impair tumor growth.

CONCLUSION

Our data suggestedthat NEK2wasimportant inregulating ccRCC cell proliferation and metastasis, and indicated NEK2as a potentially important target for the treatment ofccRCC.

Integrative analysis of transcriptomic landscape and urinary signature reveals prognostic biomarkers for clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT) have poor prognosis. We aimed to reveal features of ccRCC with VTT and develop a urine-based prognostic classifier to predict ccRCC prognosis through integrative analyses of transcriptomic landscape and urinary signature.

Methods

RNA sequencing was performed in five patients with ccRCC thrombus-tumor-normal tissue triples, while mass spectrometry was performed for urine samples from 12 ccRCC and 11 healthy controls. A urine-based classifier consisting of three proteins was developed to predict patients' survival and validated in an independent cohort.

Results

Transcriptomic analysis identified 856 invasion-associated differentially expressed genes (DEGs). Furthermore, proteomic analysis showed 133 differentially expressed proteins (DEPs). Integration of transcriptomic landscape and urinary signature reveals 6 urinary detectable proteins (VSIG4, C3, GAL3ST1, TGFBI, AKR1C3, P4HB) displaying abundance changes consistent with corresponding genes in transcriptomic profiling. According to TCGA database, VSIG4, TGFBI, and P4HB were significantly overexpressed in patients with shorter survival and might be independent prognostic factors for ccRCC (all p<0.05). A prognostic classifier consisting of the three DEPs highly associated with survival performed satisfactorily in predicting overall survival (HR=2.0, p<0.01) and disease-free survival (HR=1.6, p<0.001) of ccRCC patients. The ELISA analysis of urine samples from an independent cohort confirmed the satisfied predictive power of the classifier for pathological grade (AUC=0.795, p<0.001) and stage (AUC=0.894, p<0.001).

Conclusion

Based on integrative analyses of transcriptomic landscape and urinary signature, the urine-based prognostic classifier consisting of VSIG4, TGFBI, and P4HB has satisfied predictive power of ccRCC prognosis and may facilitate ccRCC molecular subtyping and treatment.

TLR3 serves as a novel diagnostic and prognostic biomarker and is closely correlated with immune microenvironment in three types of cancer

Background: Toll-like receptor 3 (TLR3) plays an important role in both innate and adaptive immunity, but the prognostic value of TLR3 in heterogeneous tumors and the correlations between TLR3 expression and immune infiltration of heterogeneous tumors remain unclear. Methods: We investigated the expression of TLR3 in a variety of tumors and focused on the diagnostic and prognostic values of TLR3 in kidney renal clear cell carcinoma (KIRC), pancreatic adenocarcinoma (PAAD) and brain lower grade glioma (LGG) by GEPIA, DriverDBv3, UALCAN, TIMER, LinkedOmics, STRING, GeneMANIA and FunRich, as well as the possible mechanisms of TLR3 affecting tumor prognosis were discussed. Additionally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was used to validate TLR3 expression in early KIRC. We also compared the expression of TLR3 in the plasma of early KIRC patients and normal controls by enzyme linked immunosorbent assay (ELISA). Results: TLR3 expression was significantly different in multiple tumors compared with paracancerous nontumor tissues. Elevated expression of TLR3 contributed to the prolonged survival outcome in KIRC patients. Suppressed expression of TLR3 contributed to the prolonged survival outcome in LGG and PAAD patients. Moreover, TLR3 was significantly elevated in stage1, grade1 and N0 of KIRC. The expression and function of TLR3 in KIRC, LGG and PAAD were closely related to tumor immune microenvironment. TRAF6 was a key gene in the interactions between TLR3 and its interacting genes. Finally, the results of RT-qPCR and ELISA indicated that TLR3 expression levels were significantly raised in renal tissue and plasma of early KIRC patients. Conclusion: TLR3 has the potential to be a diagnostic biomarker of KIRC, LGG and PAAD as well as a biomarker for evaluating the prognosis of KIRC, LGG and PAAD, particularly for the early diagnosis of KIRC. TLR3 affects tumors mainly by acting on the immune microenvironment of KIRC, LGG and PAAD. These findings could lead to new insights into the immunotherapeutic targets for KIRC, LGG, and PAAD.

Serum albumin to globulin ratio prior to treatment as a potential non-invasive prognostic indicator for urological cancers

Background

Numerous clinical studies have reported an association between the pretreatment albumin to globulin ratio (AGR) and survival outcomes of urological cancers. However, these conclusions remain controversial. Therefore, we performed a meta-analysis to explore the prognostic value of the AGR in urinary system tumors.

Methods

We retrieved eligible studies published up to June 2022 through a comprehensive search of multiple databases. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), progression-free survival (PFS), and biochemical recurrence-free survival (BRFS) were used to evaluated the predictive effect of the AGR before treatment in urinary system tumors. Heterogeneity test, random-effects models, fixed-effects models and sensitivity tests were used for analyses.

Results

A total of 21 studies with 18,269 patients were enrolled in our meta-analysis. We found that patients with urinary system cancer with low AGR prior to treatment had poor OS [HR = 1.93, 95% CI (1.56–2.39), p < 0.001], CSS [HR = 2.22, 95% CI (1.67–2.96), p < 0.001], RFS [HR = 1.69, 95% CI (1.29–2.22), p < 0.001], and PFS [HR = 1.29, 95% CI (0.54–3.07), p < 0.001]. For prostate cancer (PCa), a low pretreatment AGR was associated with poor BRFS [HR = 1.46, 95% CI (1.28–1.67), p < 0.001]. Also, a subgroup analysis, stratified by ethnicity, cancer type, cutoff value, sample size and publication year, was conducted. The results showed that worse OS and CSS were significantly associated with these factors.

Conclusion

Our meta-analysis revealed that the AGR before treatment could be used as a non-invasive predictive biomarker to evaluate the prognosis of urological cancer patients in clinical practice.

Increased expression of the RNA-binding protein Musashi-2 is associated with immune infiltration and predicts better outcomes in ccRCC patients

RNA-binding proteins (RBPs) mainly contribute to abnormalities in posttranscriptional gene regulation. The RBP Musashi-2, an evolutionarily conserved protein, has been characterized as an oncoprotein in various tumors. However, the prognostic value and potential roles of Musashi-2 in clear cell renal cell carcinoma (ccRCC) have not yet been elucidated. In this study, we found that Musashi-2 was mainly expressed in the normal distal tubular cells and collecting duct cells of the kidneys, while its expression was significantly decreased in ccRCC. And higher expression levels of Musashi-2 indicated better overall survival (OS) in ccRCC. Furthermore, immunohistochemistry demonstrated that PD-L1 expression was negatively correlated with Musashi-2 expression, and Musashi-2 was found to be remarkably correlated with multiple immune cells and immune inhibitors, including CD8+ T cells, CD4+ T cells, regulatory T (Treg) cells, PDCD1, CTLA4, Foxp3, and LAG3. Functional enrichment analysis revealed that Musashi-2 might be involved in ccRCC metabolic reprogramming and immune infiltration and further predicted the therapeutic sensitivity of ccRCC. Taken together, Musashi-2 is a prognostic biomarker for ccRCC patients that may provide novel insights into individualized treatment strategies and guide effective immunotherapy.

Establishment of a ccRCC patient-derived chick chorioallantoic membrane model for drug testing

Clear cell renal cell carcinoma (ccRCC) is an aggressive subtype of renal cell carcinoma accounting for the majority of deaths in kidney cancer patients. Advanced ccRCC has a high mortality rate as most patients progress and develop resistance to currently approved targeted therapies, highlighting the ongoing need for adequate drug testing models to develop novel therapies. Current animal models are expensive and time-consuming. In this study, we investigated the use of the chick chorioallantoic membrane (CAM), a rapid and cost-effective model, as a complementary drug testing model for ccRCC. Our results indicated that tumor samples from ccRCC patients can be successfully cultivated on the chick chorioallantoic membrane (CAM) within 7 days while retaining their histopathological characteristics. Furthermore, treatment of ccRCC xenografts with sunitinib, a tyrosine kinase inhibitor used for the treatment of metastatic RCC, allowed us to evaluate differential responses of individual patients. Our results indicate that the CAM model is a complementary in vivo model that allows for rapid and cost-effective evaluation of ccRCC patient response to drug therapy. Therefore, this model has the potential to become a useful platform for preclinical evaluation of new targeted therapies for the treatment of ccRCC.

SIGIRR Downregulation and Interleukin-1 Signaling Intrinsic to Renal Cell Carcinoma

Renal cell carcinoma is highly inflamed, and tumor cells are embedded into a microenvironment enriched with IL1. While inflammatory pathways are well characterized in the immune system, less is known about these same pathways in epithelial cells; it is unclear if and how innate immune signals directly impact on cancer cells, and if we could we manipulate these for therapeutic purposes. To address these questions, we first focused on the inflammatory receptors belonging to the IL1- and Toll-like receptor family including negative regulators in a small cohort of 12 clear cell RCC (ccRCC) patients’ samples as compared to their coupled adjacent normal tissues. Our data demonstrated that renal epithelial cancer cells showed a specific and distinctive pattern of inflammatory receptor expression marked by a consistent downregulation of the inhibitory receptor SIGIRR mRNA. This repression was confirmed at the protein level in both cancer cell lines and primary tissues. When we analyzed in silico data of different kidney cancer histotypes, we identified the clear cell subtype as the one where SIGIRR was mostly downregulated; nonetheless, papillary and chromophobe tumor types also showed low levels as compared to their normal counterpart. RNA-sequencing analysis demonstrated that IL1 stimulation of the ccRCC cell line A498 triggered an intrinsic signature of inflammatory pathway activation characterized by the induction of distinct “pro-tumor” genes including several chemokines, the autocrine growth factor IL6, the atypical co-transcription factor NFKBIZ, and the checkpoint inhibitor PD-L1. When we looked for the macroareas most represented among the differentially expressed genes, additional clusters emerged including pathways involved in cell differentiation, angiogenesis, and wound healing. To note, SIGIRR overexpression in A498 cells dampened IL1 signaling as assessed by a reduced induction of NFKBIZ. Our results suggest that SIGIRR downregulation unleashes IL1 signaling intrinsic to tumor cells and that manipulating this pathway may be beneficial in ccRCC.

CGN Correlates With the Prognosis and Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma

This study aimed to screen and verify the important prognostic genes related to clear cell renal cell carcinoma (ccRCC) and further analyze their relationship with the immune microenvironment. Gene expression profiles from the TCGA-KIRC, GSE46699, GSE36895, and GSE16449 datasets were utilized to explore differentially co-expressed genes in ccRCC. We screened 124 differentially co-expressed genes using a weighted gene co-expression network and differential gene expression analyses. Univariate and multivariate Cox survival analyses revealed that the expressions of genes CGN, FECH, UCHL1, and WT1 were independently related to the overall survival of ccRCC patients. Kaplan–Meier survival analysis was performed, and CGN was found to have the strongest correlation with the prognosis of ccRCC patients and was consequently selected for further analyses and experimental verification. The results showed that NK cell activation, resting dendritic cells, resting monocytes, and resting mast cells were positively correlated with CGN expression; CD4+ memory activated T cells, regulatory T cells, and M0 macrophages were negatively correlated with CGN expression. Finally, using western blotting and reverse transcription polymerase chain reaction, we verified that the CGN protein level was down-regulated in ccRCC samples, which was consistent with the mRNA levels. CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.

Effects of HMGA2 gene silencing on cell cycle and apoptosis in the metastatic renal carcinoma cell line ACHN

Objective

To explore the role of high mobility group AT-hook 2 (HMGA2) in the regulation of the cell cycle and apoptosis.

Methods

The renal carcinoma cell line ACHN was transiently transfected with small interfering RNA to knock down the expression of the HMGA2 gene. Cell cycle analysis was undertaken using flow cytometry. The mRNA and protein levels of HMGA2, E2F transcription factor 1 (E2F1), cyclin D1, cyclin dependent kinase 6 (CDK6), B-cell lymphoma-2 (Bcl-2), caspase-3 and caspase-9 were analysed using reverse transcription quantitative real-time polymerase chain reaction and Western blot analysis.

Results

The mRNA and protein levels of HMGA2 were significantly higher in renal carcinoma cell lines compared with the human renal proximal tubular epithelial cell line HKC. After HMGA2 gene-specific silencing, more cells entered the G₀/G₁ phase, while fewer cells entered the G₂/M phase; and the cells exhibited early and late apoptosis. HMGA2 gene-specific silencing significantly reduced the mRNA and protein levels of E2F1, cyclin D1, CDK6 and Bcl-2; and increased the mRNA and protein levels of caspase-3 and caspase-9.

Conclusion

The HMGA2 gene may be involved in the tumorigenesis and development of renal cancer, thus inhibiting HMGA2 gene expression might provide a potential therapeutic target in the future.

piRNAs and PIWI Proteins as Diagnostic and Prognostic Markers of Genitourinary Cancers

piRNAs (PIWI-interacting RNAs) are small non-coding RNAs capable of regulation of transposon and gene expression. piRNAs utilise multiple mechanisms to affect gene expression, which makes them potentially more powerful regulators than microRNAs. The mechanisms by which piRNAs regulate transposon and gene expression include DNA methylation, histone modifications, and mRNA degradation. Genitourinary cancers (GC) are a large group of neoplasms that differ by their incidence, clinical course, biology, and prognosis for patients. Regardless of the GC type, metastatic disease remains a key therapeutic challenge, largely affecting patients’ survival rates. Recent studies indicate that piRNAs could serve as potentially useful biomarkers allowing for early cancer detection and therapeutic interventions at the stage of non-advanced tumour, improving patient’s outcomes. Furthermore, studies in prostate cancer show that piRNAs contribute to cancer progression by affecting key oncogenic pathways such as PI3K/AKT. Here, we discuss recent findings on biogenesis, mechanisms of action and the role of piRNAs and the associated PIWI proteins in GC. We also present tools that may be useful for studies on the functioning of piRNAs in cancers.

Toll-Like Receptors Serve as Biomarkers for Early Diagnosis and Prognosis Assessment of Kidney Renal Clear Cell Carcinoma by Influencing the Immune Microenvironment: Comprehensive Bioinformatics Analysis Combined With Experimental Validation

Background: Toll-like receptors (TLRs) are important initiators of innate and acquired immune responses. However, its role in kidney renal clear cell carcinoma (KIRC) remains unclear.

Methods: TLRs and their relationships with KIRC were studied in detail by ONCOMINE, UALCAN, GEPIA, cBioPortal, GeneMANIA, FunRich, LinkedOmics, TIMER and TRRUST. Moreover, we used clinical samples to verify the expressions of TLR3 and TLR4 in early stage of KIRC by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), flow cytometry (FC) and immunohistochemistry (IHC).

Results: The expression levels of TLRs in KIRC were generally different compared with adjacent normal tissues. Moreover, the expressions of TLR3 and TLR4 elevated significantly in the early stage of KIRC. Overexpressions of TLR1, TLR3, TLR4 and TLR8 in KIRC patients were associated with longer overall survival (OS), while inhibition of TLR9 expression was related to longer OS. Additionally, overexpressions of TLR1, TLR3 and TLR4 in KIRC patients were associated with longer disease free survival (DFS). There were general genetic alterations and obvious co-expression correlation of TLRs in KIRC. The PPI network between TLRs was rather complex, and the key gene connecting the TLRs interaction was MYD88. The GO analysis and KEGG pathway analysis indicated that TLRs were closely related to adaptive immunity, innate immunity and other immune-related processes. RELA, NFKB1, IRF8, IRF3 and HIF1A were key transcription factors regulating the expressions of TLRs. What’s more, the expression levels of all TLRs in KIRC were positively correlated with the infiltration levels of dendritic cells, macrophages, neutrophils, B cells, CD4⁺ T cells and CD8⁺ T cells. Finally, the results of RT-qPCR, FC and IHC confirmed that TLR3 and TLR4 were significantly elevated in the early stage of KIRC.

Conclusion: The occurrence and development of KIRC are closely related to TLRs, and TLRs have the potential to be early diagnostic biomarkers of KIRC and biomarkers for judging the prognosis and immune status of KIRC. This study may provide new insights into the selection of KIRC immunotherapy targets.

LINC01232 serves as a novel biomarker and promotes tumour progression by sponging miR-204-5p and upregulating RAB22A in clear cell renal cell carcinoma

BACKGROUND

Long non-coding RNAs (lncRNAs) are involved in the progression of various cancers, including clear cell renal cell carcinoma (ccRCC). This study aimed to investigate the expression and prognostic value of long intergenic non-protein coding RNA (LINC) 01232 in ccRCC and preliminary explore the molecular mechanism underlying the role of LINC01232 in ccRCC progression.

METHODS

Tumour tissues and adjacent normal tissues of 122 patients with ccRCC were collected in this study. The levels of LINC01232, microRNA (miR)-204-5p and RAB22A were measured by quantitative real-time PCR. The proliferation, migration and invasion of ccRCC cells were detected by cell counting kit-8 assay and Transwell assay, respectively. The interaction among LINC01232, miR-204-5p and RAB22A was confirmed by bioinformatics analysis, dual-luciferase reporter assay and Pearson correlation analysis. The association of LINC01232 and miR-204-5p with ccRCC patient survival was verified by the Kaplan-Meier method and log-rank test. The prognostic value of LINC01232 in ccRCC was confirmed by Cox regression analysis.

RESULTS

LINC01232 expression was increased in ccRCC tumour tissues and ccRCC cells and independently predicted the prognosis of ccRCC patients. In addition, LINC01232 silencing inhibited ccRCC cell proliferation, migration and invasion. Moreover, LINC01232 served as a sponge for miR-204-5p, and miR-204-5p reduction reversed the inhibitory effect of LINC01232 silencing on ccRCC cell function. Furthermore, LINC01232 could sponge miR-204-5p, causing the elevation of RAB22A in ccRCC, thereby promoting ccRCC cell function.

CONCLUSION

LINC01232 may be an independent prognostic biomarker in ccRCC and plays an oncogenic role in ccRCC progression by sponging miR-204-5p and upregulating RAB22A.

Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma

Background

To examine the value of energetic-spectrum computed tomography (spectral CT) quantitative parameters in renal cell carcinoma (RCC) microvascular angiogenesis.

Methods

The authors evaluated 32 patients with pathologically confirmed RCC who underwent triple-phase contrast-enhanced CT with spectral CT imaging mode from January 2017 to December 2019. Quantitative parameters include parameters derived from iodine concentration (IC) and water concentration (WC) of 120 keV monochromatic images. All specimens were evaluated including the microvascular density (MVD), microvascular area (MVA) and so on. The correlation between IC and WC (including average values and random values) with microvascular parameters were analyzed with Pearson or Spearman rank correlation coefficients.

Results

The MVD of all tumors was 26.00 (15.00–43.75) vessels per field at × 400 magnification. The MVD of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical phase, WCD₁, WCD₂, NWCD₂ and ICD₁ (Spearman rank correlation coefficients, r range, 0.362–0.533; all p < 0.05). The MVA of all tumors was (16.16 ± 8.98) % per field at × 400 magnification. The MVA of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical, mean WC and mean NWC in renal parenchymal phase, WCD₁, WCD₂, WCD₃, NWCD₂, and NWCD₃ (Pearson or Spearman rank correlation coefficients, r range, 0.357–0.576; all p < 0.05). Microvascular grading correlated positively with the mean NWC, mean NIC and random NIC in renal cortical phase, mean NWC in renal parenchymal phase, NWCD₂, WCD₃, NWCD₃, NICD₂ and NICD₃ (Spearman rank correlation coefficients, r range, 0.367–0.520; all p < 0.05). As for tumor diameter (55.19 ± 19.15), μm, only NWCD₃ was associated with it (Spearman rank correlation coefficients, r = 0.388; p < 0.05).

Conclusions

ICD and WCD of spectral CT have a potential for evaluating RCC microvascular angiogenesis. MVD, MVA and microvascular grade showed moderate positive correlation with ICD and WCD. ICD displayed more relevant than that of WCD. The parameters of renal cortical phase were the best in three phases. NICD and NWCD manifested stronger correlation with microvascular parameters than that of ICD and WCD.